1. Field of the Invention
The present invention relates to fire detection system and more particularly, to a multi-wavelength video image fire detecting system comprised of a multi-wavelength video image fire detector, an alarm and indicate equipment, a setting and debugging system, a communication equipment, an area alarm and monitor system, and a pan & title and control system, wherein the multi-wavelength video image fire detector is comprised of a color and near IR dual-mode camera, a color and B/W dual-mode camera, an image capture module, a processor and controller, an I/O module, a housing and a visible light and near IR view window. The system integrates multi-wavelength smoke and flame detection algorithms and fire data fusion algorithm, satisfying different fire detection requirements under different illumination conditions.
2. Description of the Related Art
Following fast and continuous establishment of industrial, business and home buildings, the number fire accident cases is increased. In recent years, due to significant change of global weather, forest fire reports are frequently heard, bringing catastrophes to people. Many fire detection and alarm systems have been created for fire protection. However, conventional detectors for fire protection have a delayed response problem. For example, there is a time delay before transmission of heat and smoke from the location of the fire to the thermal and smoke detectors. Even a satellite fire monitoring technique us employed, it can only detect a big area fire. Air sampling smoke detectors may be used to reduce delay in detection. However, these conventional air sampling smoke detectors cannot eliminate the problem of detection delay when used for a big area protection. Only the use of video-based flame and smoke detectors can eliminate detection delay problem and give an instant alarm.
U.S. Pat. No. 6,937,743 discloses a method for automatically detecting fires, based on flame and/or smoke recognition by analyzing a sequence of images. The analysis is based on several image processing algorithms. One algorithm consists in comparing the frequency content of at least an image of the sequence with the frequency content of a reference image so as to detect an attenuation of high frequencies independently of variations on other portions of the spectrum. U.S. Pat. No. 7,002,478 discloses a method of operating a computer for smoke and flame detection comprising the steps of: receiving digitized images of the region to be monitored; comparing pixels of one of the images with pixels of another image according to two predetermined procedures to produce a flame present decision and a smoke present decision; and providing a fire detected signal according to said smoke present and flame present decisions.
The aforesaid video image-based fire detection methods rely upon visible features of the fire, such as dimension, motion, transparency, continuity, and etc. These features are detectable by conventional video-based fire detection devices only they are under a visible environment or background. Obviously, there is a limitation. Any algorithm cannot achieve the expected result if the system cannot detect smoke and flame features under all different conditions.
The prior art fire detecting systems cannot detect a field fire where the color and light intensity of the background are similar to the fire. For example, conventional fire detecting systems cannot detect an alcohol fire transparent flame, an alcohol fire obstructed flame, a wind obstructed flame, a blue flame in a blue background, a grey smoke or smoke in a grey or dark background, or a flame in a moving vehicle. Conventional fire detecting systems may produce a false alarm upon detection of a mimic flame features such as sunlight or moonlight reflecting on a wave, a moving person wearing an orange sportswear, or tree leaves oscillating in the wind. Steam, controlled fire, or smoke-like cloud may cause a conventional fire detecting system to produce a false alarm.
Further, conventional fire detecting systems have other drawbacks. Many factors in a video camera system, including type of image sensor, focal distance of lens, aperture, and white balance affect image quality. When detecting a flame under a normal condition, small aperture and compensation are better to that a clear contour of the flame can be obtained. However, the detection of a smoke is different. Because a smoke is shown in a grey, black or dark tone, aperture and compensation values should be relatively greater. More particularly, when catching the image of a smoke at night, relatively greater aperture and compensation values are necessary. If a camera parameter is added to the control algorithm of a video image-based fire detecting system, the calculation will be complicated. Theoretically, using a camera system having a fixed spectrum characteristic cannot satisfy the requirements for concomitant flame and smoke detection and alarm.
A thermal imaging system may be used for fire detection. However, a thermal imaging system usually utilizes long wavelength or middle wavelength infrared sensors. These sensors have the drawback of high cost. A thermal imaging system shows better flame and overhead detection performance, however it cannot detect a smoke or blocked flame.
Conventional fire detecting systems still have a common problem, i.e., the problem of fixed field of view. Because variable field of view will complicate the algorithm and cause an alarm report delay, conventional fire detecting systems do not adopt variable field of view. However, for forest fire detection, variable field of view is requisite.
Therefore, it is desirable to provide a multi-wavelength video image fire detecting system that eliminates the aforesaid various drawbacks of the prior art designs.